Model dynamics at the whole body level.

<p>Each plot represents one variable dynamics. The normal glucose regulation (NGR) and T2DM conditions are shown in green and black, respectively. The red and blue lines delimit the physiological lower and upper ranges of variables (see also Table B in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190627#pone.0190627.s001" target="_blank">S1 File</a>).</p

Graphical representation of the whole-body glucose metabolism as considered in our model, according to the notation introduced in [62].

<p>Only the organs/tissues for which a variable has been explicitly included in the model are depicted in the figure (other key organs/tissues of glucose metabolism, like pancreas and brain, are not displayed in the figure even if their effect has been indirectly taken into account in model equations, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190627#sec006" target="_blank">Results</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190627#pone.0190627.s001" target="_blank">S1 File</a> for details). Adipose tissue is colored in yellow to highlight that it is the part for which a model at the cellular level is also provided (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190627#pone.0190627.g002" target="_blank">Fig 2</a>). Green ovals (hormones) and orange rectangles represent model variables; arrows represent mass transfer (white head), stimulation (black head) and inhibition (T head).</p

Model simulation and data fitting, normal glucose regulation (NGR) condition.

<p>Each plot represents the corresponding time courses for the indicated insulin signaling intermediaries. The experimental data are taken from Nyman <i>et al</i>. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190627#pone.0190627.ref026" target="_blank">26</a>] and are represented with circles and error bars (a.u. indicates arbitrary units). The time course represents the model simulation.</p

A closed-loop multi-level model of glucose homeostasis

<div><p>Background</p><p>The pathophysiologic processes underlying the regulation of glucose homeostasis are considerably complex at both cellular and systemic level. A comprehensive and structured specification for the several layers of abstraction of glucose metabolism is often elusive, an issue currently solvable with the hierarchical description provided by multi-level models. In this study we propose a multi-level closed-loop model of whole-body glucose homeostasis, coupled with the molecular specifications of the insulin signaling cascade in adipocytes, under the experimental conditions of normal glucose regulation and type 2 diabetes.</p><p>Methodology/Principal findings</p><p>The ordinary differential equations of the model, describing the dynamics of glucose and key regulatory hormones and their reciprocal interactions among gut, liver, muscle and adipose tissue, were designed for being embedded in a modular, hierarchical structure. The closed-loop model structure allowed self-sustained simulations to represent an ideal <i>in silico</i> subject that adjusts its own metabolism to the fasting and feeding states, depending on the hormonal context and invariant to circadian fluctuations. The cellular level of the model provided a seamless dynamic description of the molecular mechanisms downstream the insulin receptor in the adipocytes by accounting for variations in the surrounding metabolic context.</p><p>Conclusions/Significance</p><p>The combination of a multi-level and closed-loop modeling approach provided a fair dynamic description of the core determinants of glucose homeostasis at both cellular and systemic scales. This model architecture is intrinsically open to incorporate supplementary layers of specifications describing further individual components influencing glucose metabolism.</p></div

Model simulation and data fitting, T2DM condition.

<p>Each plot represents the corresponding time courses for the indicated insulin signaling intermediaries. The experimental data are taken from Nyman <i>et al</i>. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0190627#pone.0190627.ref026" target="_blank">26</a>] and are represented with circles and error bars (a.u. indicates arbitrary units). The time course represents the model simulation.</p

Graphical representation of the model describing the insulin signaling in adipocytes at the cellular level, according to the notation introduced in [62].

<p>Solid arrows represent state modification, while dashed arrows indicate reaction stimulation. Protein complexes are colored in yellow, green ovals represent the active and inactive feedback protein, while the orange rectangles represent all the other components of the cellular model. The plasma membrane of the adipose cell is represented in yellow and it separates the cytosol (light yellow horizontal lines) from the interstitial fluid (blue and white vertical lines). The variables I and G indicate insulin and glucose concentration in plasma (compartment not represented), which regulate the amount of interstitial insulin (INS_A) and glucose (Gt_A), respectively. For the sake of simplicity, we highlighted the five variables linking the cellular level to the whole body description (namely plasma insulin, interstitial insulin, plasma glucose, interstitial glucose and intra-adipocitary glucose) by adding the corresponding names in parenthesis.</p

Model dynamics of the insulin signaling in adipocytes at the cellular level (only a subset of key variables is represented).

<p>The normal glucose regulation (NGR) and T2DM conditions are shown in green and black, respectively.</p

Combined use of protein biomarkers and network analysis unveils deregulated regulatory circuits in Duchenne muscular dystrophy

<div><p>Although the genetic basis of Duchenne muscular dystrophy has been known for almost thirty years, the cellular and molecular mechanisms characterizing the disease are not completely understood and an efficacious treatment remains to be developed. In this study we analyzed proteomics data obtained with the SomaLogic technology from blood serum of a cohort of patients and matched healthy subjects. We developed a workflow based on biomarker identification and network-based pathway analysis that allowed us to describe different deregulated pathways. In addition to muscle-related functions, we identified other biological processes such as apoptosis, signaling in the immune system and neurotrophin signaling as significantly modulated in patients compared with controls. Moreover, our network-based analysis identified the involvement of FoxO transcription factors as putative regulators of different pathways. On the whole, this study provided a global view of the molecular processes involved in Duchenne muscular dystrophy that are decipherable from serum proteome.</p></div

Long biomarker panel.

<p>Long biomarker panel.</p

Tissue specificity from Human Protein Atlas.

<p>(a) Bar chart showing the number of proteins in each of the categories defined by Human Protein Atlas to classify the proteins according to their level of tissue-specificity. (b) Bar chart showing the tissues in which the tissue-enriched proteins are expressed. The stars above the columns indicate the significance of enrichment analysis (***Fisher’s exact test p-value < 0.0001; ** Fisher’s exact test p-value < 0.001).</p